Heat capacity (Cp) effects have assumed a central importance in the understanding of the hydrophobic effect, in the determination of protein stability as a function of temperature and amino acid composition, and in the dissection of the energetics of protein folding and protein-DNA binding. Most heat capacity effects come from macromolecule-solvent interactions. The solvent contribution is well characterized experimentally for proteins, but even the simplest features, such as the opposite sign of the polar and nonpolar hydration Cp, remain unexplained at a fundamental level. Empirical area and group dependence analyses are widely used to separate out Cp contributions in proteins, but without a better theoretical understanding, it is not known when such approaches may fail in the complex environment of proteins and DNA. This project is designed to address some of these gaps in methodology and understanding, specifically to use a method based on a combination of the random network (RN) and explicit water models to understand hydraption Cp changes at a quantitative and molecular level. Previous studies using the RN model on a polar and a nonpolar solute have shown i) why, in terms of changes in water structure around the solute, the hydration heat capacity for apolar and polar solvation is of opposite signs ii) that the method can be used for quantitative study of solute-solvent heat capacity effects. Proceeding with compounds that contain both polar and non-polar groups Dr. Sharp aims to study the additivity of Cp, how the competing hydration shells of the different groups interact, and if and when the additivity assumptions might breakdown. In the course of these studies, Dr. Sharp aims to i) develop a rapid way to calculate hydration Cp that is more accurate than simple area or group methods, but does not involve explicit water simulations for each system. The method for calculating hydration cp will be applied to ii) nucleic acid-protein binding, in order to better understand the balance of entropic and enthalpic interactions, and the balance of solvation and intermolecular energies. iii) analysis of the water around antifreeze proteins (AEP). This will be used to address the question of what are the unique properties of AFP and its interaction with water that allow it to function as an antifreeze. iv) The approach will also be extended to calculation of hydration G, S & H. An implicit solvation model of this type has many uses in macromolecular simulations. The study of protein-DNA interactions has direct applications to a better understanding of gene regulation, which in turn has many applications to understanding cellular function in normal and diseased states.